In today’s media-savvy basketball world, there are a number of methods available to analysts like myself to evaluate players, teams, lineups and everything in between. As part of our natural human tendency, in many cases we gravitate toward more comprehensive measures, particularly in terms of individual player analysis; metrics like PER or Win Shares were created in this vein, an attempt to quantify an all-encompassing view of a player’s statistical contributions within a single number.

Frequently, though, we require more context.

With this in mind, let’s take a small bite from the proverbial Jazz analytics pie. Last week, the recently-launched Nylon Calculus (the new analytics arm of Hardwood Paroxysm under the Sports Illustrated banner, for which I am also a contributor) debuted a remarkable advancement in shot chart data from my colleague Austin Clemens1. Those who enjoy pieces from Kirk Goldsberry on Grantland are in heaven, as NC now hosts the capability for anyone and everyone to create very similarly-styled shot charts for any player in the league, dating all the way back to the 1996-97 season. Let’s look at Gordon Hayward’s chart from last season as an example:

As the legend at the bottom explains, colors by area reflect the player’s field-goal percentage from that area compared to league average for the given year – red is better, blue is worse. The size of the cubes reflect the frequency of shots from each location, and printed numbers inside certain cubes reflect actual field-goal percentage from that area rather than percentage compared to league average.

Got it? Good. Now let’s apply it to our Jazz. What follows is a look at several of Utah’s more important pieces through the lens of Austin’s charts, with bits of relevant context to further paint the picture. Because I already took a detailed look at Hayward for NC last week, he’ll be left out.

Trey Burke:

This particular set of glasses isn’t too rosy as far as Trey was concerned in his rookie season. Of particular worry to me isn’t necessarily the amount of blue in his chart, but rather how spread out it all is. Burke was chucking from everywhere, despite being efficient compared with his peers in only a few areas of the court – as he develops, Jazz fans will hope he identifies his strongest areas and works to generate higher volume from them while eliminating some of the fluff from his selection. His work from midrange was scattered, though he was solid from both the left and right elbow, a promising sign going forward for his off-the-bounce game coming out of the pick-and-roll. His strange side-to-side disparity, particularly from the baseline midrange and corner 3’s, is likely a result of variance within a small sample – he attempted just 24 corner 3’s from the left and 15 from the right, per NBA.com, so just a few makes or misses would swing his percentages here in a large way.

Most worrying were his percentages from the high-emphasis areas in today’s NBA, at the rim and from deep. Trey hoisted 293 non-corner 3’s last year, shooting just 32.8 percent on them, and apart from a couple small clusters had virtually no reliable areas as a distance threat. Utah’s generally poor spacing certainly contributed to a degree, but it’s also not as though he was forced to take high-volume stepbacks or off-the-bounce triples – over 82 percent of his non-corner makes were assisted. Things were equally grim at the basket, where Burke simply wasn’t efficient finishing against NBA length. This isn’t uncommon for young guards, but given his general lack of explosiveness it may be a concern for Trey throughout his career, and he’ll surely be spending time this offseason working on angles and shielding the ball more effectively. As he moves forward with his career, much like many of his young teammates, expect his selectivity and accuracy to improve as he becomes more comfortable with the pro game in all aspects.

Alec Burks:

Like his similarly-named backcourt counterpart, Burks needs to improve his selection a bit, though not to nearly the same degree. Part of this is his time in the league already, as he’s developed in this area significantly from his first couple years. I wrote back in February about, among other things, his divisive splits from the left and right sides, and Austin’s chart only reinforces this idea2 – he’s significantly better going to his right than his left. This is an exploitable tendency for smart defenses until he can smooth it out somewhat, but credit to Alec for emphasizing his right more often, as shown by the larger clusters there.

The reversal of this trend around the basket is likely representative of his strong athleticism and cutting, as well as an ability to finish through contact even on his weaker side:

He’ll want to improve on his stronger hand here, but on the surface this seems far easier for a player with his kind of physical ability than rapidly improving his weaker side. But overall, especially given Utah’s numerous offensive issues last year, fans should be quite encouraged with Burks’ chart, particularly if he continues to improve from deep.

Derrick Favors:

Favors has the easiest chart to dissect, by a decent amount. Like Burks, he reined in some of his lesser efficiency shots from the previous year, in particular basically eliminating shots outside 16 feet (he took just 57 all year). I’ve discussed his jump-shooting in this space before, and while it continues to make small strides over previous years, it’s likely Derrick’s largest obstacle as a player going forward. He’s a strong finisher around the rim and will continue to be given his athleticism, but a leap in his midrange efficiency, and particularly an evening out of both his attempts and accuracy from each side of the block, could be the element that really pushes him into borderline star territory at his position. The upcoming couple years will be huge in this regard for Favors, who can well exceed the value of his recent contract extension and put himself in position for a big raise down the line if he can reach average or above average.

Enes Kanter:

Kanter’s eye test is reflected almost exactly in his jump-shooting clusters on the chart – lethal from the left baseline and slightly closer in on the right baseline, mostly lukewarm from “floater”-type range. His selection is likely the best of Utah’s young core; his highest efficiency areas, for the most part, are his highest volume as well. He shot nearly 39 percent from all midrange shots, and was Utah’s most consistent threat from here all year long. He could do to improve from those little in-between areas outside the restricted area, but to my eye much of this is mental – he rushes shots in these areas, particularly after offensive rebounds, and doesn’t collect his balance enough, areas he can easily improve with age.

Slightly surprising when compared with the eye test are his figures around the hoop. Stuck in my mind are frequent examples of Kanter hesitating on close looks and making life around the basket more difficult for himself, but the numbers bear him out as closer to average than I’d have guessed. Of 67 centers attempting at least 100 shots in the restricted area last season, Kanter’s 62.4 percent puts him 41st, nowhere close to elite but certainly higher than I’d have pegged him on a raw guess3. As he improves his confidence and strength while retaining his superb footwork and post game, expect these numbers to continue to rise.

Jeremy Evans:

Despite being a fan favorite and by all accounts one of the nicest guys in the game, Evans’ chart goes a long way toward showing why he’s been unable to find a consistent place in Utah’s rotation. He just hasn’t fully figured out who he is as an NBA player yet, as evidenced by his largely spread out shot locations and his only real clustering taking place around the basket. He expanded his range extensively last year in a more untethered role for the first time in his career, but just didn’t prove effective enough in any of these new areas to warrant real attention from defenses. He remains a beast around the hoop given his ridiculous hops, but his lack of another reliable shot and inability to hold his own down low against bulkier bigs4 may see the upcoming year as his last in a Jazz uniform.

Ben Dowsett

Ben Dowsett is a life-long Jazz fan and general sports fanatic based in Salt Lake City. He also writes for Nylon Calculus (Hardwood Paroxysm/Fansided Network), and can be heard on the airwaves for the SCH podcast and appearances with ESPN AM 700. With a strong background in both statistics and on-court fundemantals, he writes primarily as an in-depth strategic analyst. He can be found on Twitter at @Ben_Dowsett.

19 Comments

Snyder is going to work closely with Burke, Burks, and Exum on finishing at the rim. He’ll learn them to play the game well. Hayward better learn how to shoot the corner three, he’ll be getting a lot of those this next year.

Nice article. I’m not sure why you are optimistic about Burks shot chart though. I guess it’s good that he has some spots where he can make jumpers at or above the league average, but look at all that blue at the hoop. That’s his bread and butter and it looks like he’s not even above average at it.

What gotag said, plus his development over previous seasons despite playing on a markedly worse offensive team with a larger individual burden. Also, very few guards above average for the entire league everywhere at the rim with skew created by bigs who do nothing but dunk – frequency is more important in most cases (also because of fouls, as gotag says), and he’s well above average there.

Actually, I’ve been looking at other wing shot charts and Burks is not that good at the rim which is surprising. Look at Kawhi Leonards or Lance Stevensons or Matt Barns for example. He definitely is living at the line. There is a big discrepancy in his TS% and eF%.

I’m not saying he’s bad or doesn’t have a lot of promise, I’m just surprised that he is not that efficient at the rim.

I think that’s pretty exaggerated, if not just false – of 99 guards attempting at least 100 shots in the restricted area last year, he was 38th in percentage. Not elite, but better than “not that good.” Also, per SportVU, he scored 8.0 points-per-48 on drives, which is tied for 11th of 273 rotation players who played at least 50 games last year. And as you’ll know from watching him, he gets to the rim on nearly all of these. One small flaw of charts like Austin’s are that for guys like Alec who get there so often, the basket area often gets very crowded and potentially noisy. He’s doing fine there, especially given he was Utah’s only real driving threat last year (should change in short order with Exum and a better penetrating system) and was creating most of his own lanes to the hoop.

So it’s a problem of reconciling all the stats. Were do you get the 38th percentile stat? Hoopdata definitely have him at %60 at the rim which by my rough estimation is below average for shooting guards. ANd the chart seems to confirm that number and there were plenty of wings with more red at the hoop than Alec. Does that SportVU number include foul shots? If so, then it doesn’t tell us about his finishing.

And now I just looked at 82games and their at the rim percentages are 67%

And then I went to NBA.com and on his shot chart, which includes a larger area that just rim to 3 ft, he shoots 54%. And player tracking only has info for something like the top 15 teams, so no sportVU info on Burks, at least that I can find.

If there’s ever a question, you should always trust the league site (NBA.com) – I wasn’t even aware Hoopdata was in operation this year, thought it shut down a year ago, and while sites like 82games can be useful they are also nowhere near as reliable as the actual league stats. League stats are also far more detailed and allow you to do more than make rough estimations like you state. Also, shot charts on NBA.com are solid and accurate, but for actual percentages compared with peers, you need to go to the “League” tab and “Stats by Player” and “Player Shots”, then use the variety of filtering capabilities (in this case I used position and FGA in RA) to filter down for the search terms you want – I also change the “Distance” filter to “By Zone” rather than “5 ft” or “8 ft”, find it’s more informative breaking down RA, ITP (Non-RA), Midrange, Corner 3 and ATB 3.

That’s where I pulled his 38th rank of 99 guards attempting at least 100 restricted area shots from, it’s very easy to do. It’s not the 38th percentile, just 38th ranked out of 99 players. I can change these filters however I want – for example, if I change it to 300 or more restricted area shots attempted last year, only 19 guards appear, and Burks ranks 7th in RA FG% of these 19, extremely narrowly behind elite finishers like Tony Parker and Monta Ellis (both are <1% better). Being in the upper half of super high-volume guards in the Restricted Area is definitely not a bad sign for his rim finishing.

You need to also pay more careful attention to the tabs on top, in this case for “Regular Season” or “Playoffs” – you’re only finding 16 teams because your tab is set to “Playoffs” As far as I’m aware, SportVU does not track fouls in their driving statistics, but this is a picture we can easily paint in other ways, such as the difference you noted between his eFG% and his TS% along with other simple methods like his foul rate for guards league-wide that gotag cited above (I haven’t actually confirmed this figure but know it’s high). Again, Alec is just fine as a rim finisher, especially to his weaker left side, and the numbers clearly bear this out. He’s not LeBron or John Wall, but he’s also not paid like them. He also turned 23 a week ago and will continue to improve things like his balance and selectivity at the rim. Plus, all my caveats from my last response about his role as Utah’s only legit penetrator still obviously apply – he’s fine, significantly better than fine depending on how you want to look at it.

OK. I got the sportsVU stuff to work. I had it on playoffs instead of regular season. Of the guys that drove five or more times a game, Burks came in at 29 out of 58 for fg%. But then, as you say when you sort by points per drive per 48, he comes in 14 out of 58, the difference being fouls.

So amongst frequent drivers, he is exactly average at finishing, but very good at getting fouled.

He shoots 47% on drives but 75% on FT. So every time he gets fouled its a bonus. Which makes that shot chart misleading in Burks case and means that you guys were right.

So he needs to keep driving and improve his shot selection and foul shooting and he can bump his efficiency way up.

Unless I’m mistaken, the difference between his FG% and his per-48 scoring on drives is not fouls, it’s the fact that he played less minutes per game than nearly anyone else near the top of those lists. He was simply creating more points per minute than most of them, as indicated by his high ranking there. Again unless I’m wrong, SportVU stats are a player tracker only and do not include free throws in their calculations, though I can’t say this with 100% certainty. Also, given the amount of noise for stats like these, you’d do well to avoid absolute statements like your second paragraph – getting an EXACT read on a player using only player tracking is not possible with the current level of information we have.

I see now about the per-48 but does Team PPG on drives include fouls? Or assists? What am I missing here? They have to be including something else becasue that number is always bigger than Player PPG on drives.

I tried to reconcile Player PPG on drives by multiplying drives per game by two (potential points) and then multiplying that by the shooting percentage which should = player PPD, but the numbers I get doesn’t match the number they have.So it SEEMS like they are including assists or fouls (or I’m not dong the math right or there is some kind of fraction of games issue or something).

I don’t know. But it does seem like fouls and assists SHOULD be included, somewhere.

No wait! I’m getting dizzy here. My formula for getting Player PPG per drive yeilds a BIGGER number than the NBA number, so they are NOT including assists or fouls in player PPG per drive. Who knows what they are doing with the team thing.